Recently, the number of people suffering from sleep disorders including chronic insomnia has become significant, and traffic accidents caused by dozing are also frequent. Furthermore, although it is required to reduce the work load of nursing care for the elderly, with respect to the aging society which is rapidly advancing, it is not easy to reduce the work load due to resistance such as an elderly person wandering late at night that cannot be predicted, and erroneous timings of changing diapers of an elderly person and calling an elderly person to wake up. There is a possibility that these circumstances can be improved by properly determining the state of sleep and making actions appropriately.
As a method for estimating the sleep stage, a sleep polygraph test based on international standards for sleep stage classification by Rechtschaffen & Kales is known (Non Patent Literature 1). In this method, a special instrument is attached to a subject lying in a bed, data of EEG (electroencephalogram), EMG (electromyogram), and EOG (eye movement) are acquired, and the sleep stage is determined based on the expertise and the experience of the a doctor. However, to wear a special instrument is a heavy load on the subject, particularly, it is unrealistic for an elderly person to wear a special instrument all night.
Therefore, there has been proposed a method of measuring data of the body (heartbeat, respiration, and body movement) without directly attaching an instrument to the subject, and acquiring, from the measured data, data that can be approximated to the temporal transition data of sleep stages obtained by a sleep polygraph test. For example, Watanabe et al. have developed an unrestrained air mattress type sensor capable of measuring body data (heartbeat, respiration, and body movement), and have devised a method of determining the sleep stage from the obtained data (Patent Literature 1, Non Patent Literature 2).
Furthermore, Takadama et al. have devised a method of estimating the sleep stage by appropriately filtering data of the heartbeat obtained from an unrestrained type sensor (Non Patent Literature 3, Patent Literature 2, and Non Patent Literature 4).
Note that the principle of estimating the sleep stage from the data of the heartbeat is based on a number of findings indicating that there is a strong correlation between the medium frequency component of the heartbeat and the sleep stage (Non Patent Literature 5, Non Patent Literature 6).